import tensorflow as tf
import numpy as np
#save
'''
## Save to file
#remember to define the same dtype and shape when restore
W=tf.Variable([[1,2,3],[3,4,5]],dtype=tf.float32,name='W_weight')
b=tf.Variable([[1,2,3]],dtype=tf.float32)

init=tf.initialize_all_variables()


saver=tf.train.Saver()


with tf.Session() as sess:
     sess.run(init)
     save_path=saver.save(sess,"my_net/save_net.ckpt")
     print("Save to path:",save_path)

'''
#restore variables
#redifine the same shape and the same type for your variables

#W=tf.Variable(np.arange(6).reshape((2,3)),dtype=tf.float32,name='weights')
W=tf.Variable(np.arange(6).reshape((2,3)),dtype=tf.float32,name='W_weight')
#b=tf.Variable(np.arange(3).reshape((1,3)),dtype=tf.float32)

#not need init step


saver=tf.train.Saver()

with tf.Session() as sess:
     saver.restore(sess,"my_net/save_net.ckpt")
     b=tf.Variable(np.arange(3),tf.float32)
     init=tf.initialize_all_variables()
     sess.run(init)
     print("weights:",sess.run(W))
    
     print("biases:",sess.run(b))

